CompareClassification: Compare two classification maps
In greenbrown: Land Surface Phenology and Trend Analysis

Description Usage Arguments Value Author(s) See Also Examples

This function computes an agreement map of two classifications (RasterLayers with classified values). Additionally, it computes a frequency table with user, producer and total accuracies as well as the Kappa coefficient.

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CompareClassification(x, 
    y, names = NULL, 
    samplefrac = 1)

`x`	First raster layer with classification.
`y`	Second raster layer with classification.
`names`	a list with `names` of the two classifications and class `names`. See example section for details.
`samplefrac`	fraction of grid cells to be sampled from both rasters in order to calculate the contingency table

The function returns a list of class "CompareClassification" with the following components:

raster a raster layer indicating the agreement of the two classifications.
table a contingency table with user, producer and total accuracies. Rows in the table correpond to the classification x, columns to the classifcation y.
kappa Kappa coefficient.

Matthias Forkel <matthias.forkel@tu-dresden.de> [aut, cre]

plot.CompareClassification, AccuracyAssessment, TrendClassification

# Calculate NDVI trends from two methods and compare the significant trends

# # calculate trends with two different methods
# AATmap <- TrendRaster(ndvimap, start=c(1982, 1), freq=12, method="AAT", breaks=0)
# plot(AATmap)
# STMmap <- TrendRaster(ndvimap, start=c(1982, 1), freq=12, method="STM", breaks=0)
# plot(STMmap)
# 
# # classify the trend estimates from the two methods into significant 
# # positive, negative and no trend
# AATmap.cl <- TrendClassification(AATmap)
# plot(AATmap.cl, col=brgr.colors(3))
# STMmap.cl <- TrendClassification(STMmap)
# plot(STMmap.cl, col=brgr.colors(3))
# 
# # compare the two classifications
# compare <- CompareClassification(x=AATmap.cl, y=STMmap.cl, 
#    names=list('AAT'=c("Br", "No", "Gr"), 'STM'=c("Br", "No", "Gr")))
# compare
# 
# # plot the comparison
# plot(compare)